Electronic blood pressure measurment device

ABSTRACT

In an electronic blood pressure measurement device which is arranged to extract pulse waves from the measured cuff pressure, a pulse wave pattern is generated from the pulse wave amplitude and pulse wave interval data and this pulse wave pattern is compared with reference patterns to classify the pattern in order to accurately obtain biological information other than the blood pressure. Blood pressure amplitudes PA(i) are computed from the measured cuff pressures C(i) and a pulse wave pattern is generated (35) on the basis of this pulse wave amplitude data and this pulse wave pattern is classified into a plurality of reference patterns (37) according to reference patterns or reference values (36). Here, the reference patterns or reference values are set as hemodynamic references based on dynamic characteristics of the blood vessel or cardiac output characteristics. The pulse wave pattern is normalized as necessary to extract only the shape factors of the pattern, is displayed as a measured pattern corresponding to a reference pattern and is compared with the reference patterns in terms of shape. Also, besides the shape factors, the absolute values of pulse wave amplitudes and systolic pressures are used as references for pattern classification.

TECHNICAL FIELD

The present invention relates to an electronic blood pressuremeasurement device which detects the cuff pressure for the evaluation ofvascular dynamics and is concerned in particular with an improved devicefor obtaining biological information besides blood pressure, etc. on thebasis of pulse wave components extracted from the cuff pressure.

PRIOR ARTS

Conventional devices for non-invasive measurement of vascular dynamicsinclude that which detects the Korotkoff's sound that is generated bythe pulse waves within the blood vessels during the process of graduallydecreasing the pressure of a pressurized cuff. In such a device, thepressures at the points in time at which the Korotkoff's sound isgenerated, becomes the maximum and disappears are detected to obtain thesystolic blood pressure, the mean blood pressure and the diastolic bloodpressure. However, detection errors occur easily in this method sincethe Korotkoff's sound is a minute sound in a frequency band that iseasily influenced by external noise and this method has such problems aslarge detection errors and poor reproducibility since the decay of soundwaves differ greatly according to the detected part and the thickness ofthe superficial tissue.

Thus, in recent years, the oscillometric method has come to be used inwhich the blood pressure, etc. are directly computed from the variationsin the cuff pressure. In this method, the pulse waves that are overlaidonto the detected cuff pressure are extracted to derive the amplitudesof the pulse waves and the pressures at the points at which the pulsewave amplitude is the maximum, at which the amplitude is a predeterminedproportion of the maximum value at the higher pressure side of themaximum and at which the amplitude is a predetermined proportion of themaximum pressure at the lower pressure side of the maximum aredetermined as the mean blood pressure, systolic blood pressure anddiastolic blood pressure, respectively. Sphygmomanometers that use thismethod are not easily affected by external influences such as externalnoise and vibration and enable measurements of high accuracy andreproducibility since highly sensitive pressure sensors can be used andsince the detected signals are in a low frequency band.

Most of the measurement devices of the said type perform only thedetection of the systolic pressure, the diastolic pressure, the meanblood pressure and the pulse rate. However, since these values areinfluenced by various factors such as cardiac output and degree ofhardening of the arteries and the influence of such factors cannot bejudged by simply measuring the blood pressure, it is not only impossibleto correctly evaluate the blood pressure value but it is also impossibleto obtain a correct understanding of the vascular dynamics.

Also, particularly in the case of measurement devices using theoscillometric method, the blood pressure values are computed generallyby a predetermined method that is based on comparison with a directmethod such as that in which a catheter is inserted. However, such amethod has a problem in that, due to variations in the pattern of pulsewave amplitudes, cases arise that do not correspond with values detectedby the direct method.

Furthermore, the mechanism of generation of Korotkoff's sounds and pulsewave amplitudes has not been investigated in detail and the presentcircumstances are such that the relationships between measured data andthe cause thereof are judged experientially and case by case.

The present invention is one that solves the said problems and thepurpose thereof is to provide a measurement device that can extractinformation reflecting the vascular dynamics from pulse wave amplitudepatterns on the basis of the knowledge obtained through theclarification of the mechanism of generation of pulse amplitudes toprovide indications for such measured values as the blood pressure.

DISCLOSURE OF THE INVENTION

The present invention provides a pressure detection means (12, 16,17:23) that detects the cuff pressure under the influence of the pulsewave during the process of gradually decreasing or increasing the cuffpressure, a pulse wave extraction means (24) that extracts the pulsewave components from the cuff pressure detected by said pressuredetection means, a pulse wave amplitude detection means (27) thatdetects the pulse wave amplitudes which express the values correspondingto the amplitude of each pulse of the pulse wave component extracted bysaid pulse wave extraction means and a pattern classification means (37)that classifies the pulse wave patterns, that express the pulse waveamplitude variations on the basis of the pulse wave amplitudes,according to reference patterns that are set as hemodynamic referencesbased on dynamic characteristics of blood vessels and/or cardiac outputcharacteristics. Thus, by the present invention, not only are pulse wavepatterns used simply to judge the blood pressure values as was doneconventionally, but it also becomes possible to extract informationreflecting the vascular dynamics by the classification of pulse wavepatterns according to the shapes of the patterns. It also becomespossible to know the meaning and the reliability of the blood pressurevalue judged by the shape of the pulse wave pattern.

A pulse wave pattern generation means (32, 33, 35, 36, 1005, 1006), thatgenerates pulse wave patterns that are normalized by predeterminedreference values on the basis of pulse wave amplitudes and pulse waveintervals, is also provided in the present invention. In this case, itis preferable to provide in the pulse wave pattern generation means, apulse wave pattern normalization means (1005, 1006) that normalizes thepulse wave amplitudes and the pulse wave intervals. Although widelyvarying pulse wave patterns are obtained due to measurement conditionsand individual differences (pulse rates, blood outputs, blood pressureamplitudes), the provision of a pulse wave pattern normalization meansenables accurate classification of patterns by enabling comparisons ofonly the shapes of the patterns.

Furthermore, it is preferable to normalize the reference pattern in thesame manner as the normalized pulse wave pattern and for the pulse wavepattern classification means to use the correlation between a pluralityof reference patterns and the normalized said pulse wave pattern as aclassification reference. Accurate pattern classification based only onthe shape of the pattern is enabled by classifying on the basis of thecorrelation with the reference patterns that are normalized in the samemanner. In particular, by using the position of the maximum value of thepulse wave amplitudes as a basis to normalize each of the said pulsewave intervals prior and subsequent to said position, errors in thecomparison of patterns due to deviations in the peak positions can beavoided.

It is preferable to set a plurality of reference patterns according tothe shape of the peak of the pulse wave amplitude. The peak shape of thepulse wave amplitude reflects information, particularly on theexpandability of the blood vessel.

It is also effective to provide a quantization means (29, 30, 31) thatquantizes the pulse wave amplitudes and/or pulse wave intervals andtransmits the quantized data to the pulse wave pattern generation means.By providing a means for quantizing the detected data, the high dataresolution, which is not necessarily required for the subsequentprocesses of pulse wave pattern generation and classification, can bereduced to some degree to enable reductions in the processing time andthe memory capacity.

In the above cases, it is preferable to provide in the patternclassification means, a means (1022) for detecting the number of peaksand/or the degree of disturbance of pulse wave patterns and to performthe classification (1023, 1024) of pulse wave patterns using the numberof peaks and/or degree of disturbance as part of the classificationreferences. The number of peaks and/or degree of disturbance accuratelycapture the anomalous conditions of the pulse wave patterns, in otherwords, the trends that reflect such symptoms as arteriosclerosis,arrhythmia and heart disease.

It is also preferable to provide in the pattern classification means, ameans (1025) for detecting the peak widths of the said pulse wavepatterns and to perform the classification (1026) of pulse wave patternsusing the peak widths as a part of the classification references. Thepeak widths reflect, in particular, conditions of the blood vesselincluding anomalies of the expandability of the blood vessel due toarteriosclerosis, fatigue caused by stress, tension, etc.

Furthermore, it is preferable to equip a blood pressure detection means(25) that detects at least the systolic pressure on the basis of thepulse wave component or the pulse wave pattern and to arrange so thatthe pulse wave pattern classification (1027, 1029) is performed at thepattern classification means by the use of the systolic pressuredetected by the blood pressure detection means as a part of theclassification references. Although there are cases wherein theclassification of wave pulse patterns cannot be performed only by theshapes of the patterns, the use of the blood pressure value as part ofthe classification references enables classification from acomprehensive standpoint.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram which shows the arrangement of asphygmomanometer in the embodiment of an electronic blood pressuremeasurement device by the present invention.

FIG. 2 is a functional block diagram which shows the processes, carriedout in said embodiment, as a combination of means of implementation ofthe functions.

FIG. 3 is an outline block diagram which shows the overall arrangementof an embodiment by the present invention.

FIG. 4 is a timing chart which shows the signal forms of the processescarried out by the MPU in the said embodiment.

FIG. 5 is a graph that shows the relationship between the transmuralpressure (the difference between the internal pressure and the outerpressure) and the variation of the volume of a blood vessel.

FIG. 6 is a graph that shows a comparison of the variations in time ofthe cuff pressure and of the pulse wave amplitude.

FIG. 7 is a graph that shows typical examples of pulse wave patterns(pattern A and pattern B).

FIG. 8 is a graph that shows a typical example of a pulse wave pattern(pattern C).

FIG. 9 is an explanatory diagram that shows typical examples (patternsA, B, C, D and E) and measured examples of pulse wave patterns and thecorresponding symptoms.

FIG. 10 is a flowchart that shows the pattern generation procedurecarried out by the pulse wave pattern generation means.

FIG. 11 is a graph that shows patterns before and after errors in thepulse wave amplitude, that were caused by body movement, etc., have beenremoved.

FIG. 12 is a graph for explaining the data interpolation and filtering(smoothing) processes.

FIG. 13 is a graph for explaining the process of normalization of pulsewave patterns.

FIG. 14 is a graph for explaining a different method of normalization.

FIG. 15 is a flowchart which shows the pattern classification procedureof the pulse wave pattern classification means.

FIG. 16 is a flowchart which shows a pattern classification procedurethat is different from that shown in FIG. 15.

FIG. 17 is a flowchart that shows, in detail, the peak and disturbancedetection procedure in the pattern classification procedure shown inFIG. 16.

FIG. 18 is a flowchart that shows, in detail, the peak width calculationprocedure in the pattern classification procedure shown in FIG. 16.

FIG. 19 is a graph which shows an example of a pulse wave patterncorresponding to pattern A for explaining the classification method of adifferent pattern classification means.

FIG. 20 is a graph which shows an example of a pulse wave patterncorresponding to pattern E for explaining the same classification methodas that in FIG. 19.

FIG. 21 is a graph which shows an example of a pulse wave patterncorresponding to pattern C for explaining the same classification methodas that in FIG. 19.

FIG. 22 is a graph which shows an example of a pulse wave patterncorresponding to pattern D for explaining the same classification methodas that in FIG. 19.

A PREFERRED EMBODIMENT OF THE INVENTION

An embodiment of an electronic blood pressure measuring device by thepresent invention shall now be described with reference to the drawings.The measuring device in the present embodiment is one which premises thederivation of pulse wave amplitudes by the oscillometric method and onein which blood pressure measurements by the oscillometric method can becarried out simultaneously. Before describing the measuring deviceitself, the measurement principles of the measuring device and therelationship between the measurement principles and the internal bodilyfactors shall be described.

The transmural pressure (the difference between the internal pressureand the outer pressure) of the blood vessel and the variation in theblood vessel volume caused by the transmural pressure determine theminute pulse wave amplitudes which are overlaid onto the cuff pressureduring the process of gradually decreasing or increasing the cuffpressure. The present inventors have found that a large non-linearityexists between the elastic modulus of the blood vessel and thetransmural pressure as shown by the solid line in FIG. 5. The variationof the blood vessel volume increases rapidly at parts where thetransmural pressure is small and the expandability of the blood vesselis the largest when the blood pressure and the internal pressure areapproximately equal, that is, when the applied cuff pressure is nearlyequal to the mean blood pressure.

Thus, pulse waves are not observed when the applied cuff pressure ishigh enough to overcome the systolic pressure at the start of thegradual pressure decreasing process and a pulse wave 1b, with a smallamplitude, results from pulse 1a and is detected only after the cuffpressure decreases somewhat. When the cuff pressure decreases further, apulse wave 2b, with a larger amplitude, is obtained as a result of pulse2a and when the cuff pressure becomes equal to the mean blood pressure,a pulse wave 3b, with the maximum amplitude, is generated as a result ofpulse 3a. As the cuff pressure decreases further, the amplitude of thepulse wave decreases (4a, 4b) and in the final stage wherein thevariation in expandability is small, pulse waves with small amplitudes(5a, 5b) are obtained.

As shown in FIG. 5, the expandability of the blood vessel is the basicfactor behind why a characteristic pulse wave amplitude pattern isobtained by a sphygmomanometer. FIG. 6 shows the relationships ofcorrespondence between the cuff pressure and the detected pulse waveamplitude. The pulse wave amplitude pattern derived from the decreasingprocess of the cuff pressure is thus a result of the non-linear property(variation in elastic modulus) of the blood vessel shown in FIG. 5 andthis non-linear property results from the blood vessel structure and thevariations thereof. That is, a blood vessel is constituted of elasticfibers formed from muscle tissue and of collagenous fibers of a lowexpandability that surround the elastic fibers. Thus, when the internalpressure applied to the blood vessel is low, the tension of the vascularwall is mainly supported by the elastic fibers and the blood vesselexhibits a large expandability. On the other hand, when the blood vesselis expanded, the blood vessel exhibits a small expandability due to therestriction of the deformation of the blood vessel by the collagenousfibers.

The pulse wave patterns, that are obtained as a result of thecharacteristics shown in FIG. 5, actually take on various shapes thatdepend on the amount of the pressure variation caused by pulses and theconditions of the blood vessel. The pulse wave amplitudes of a pulsewave pattern become large when the expandability of the blood vessel islarge and when the cardiac output is large. When a change occurs in thecondition of the blood vessel, in particular, when hardening of theelastic fibers occurs, changes occur in the expansion characteristics ofthe blood vessel, shown in FIG. 5, that lead to changes in the shape ofthe pulse wave pattern (especially the peak shape). FIG. 7 shows, incomparison, a pattern A that is obtained when the circulatory system isnormal and a pattern B that is obtained under conditions of hypotension,anemia or shock. FIG. 8 shows a pattern C, which appearscharacteristically when a sclerosing lesion or a strong tension existsat the blood vessel. Although it is often thought in such cases that thepulse wave amplitude will decrease since the elastic modulus of theblood vessel usually rises due to the lesion or tension, since these aregenerally accompanied by increases in the vascular resistance whichleads to a rise in the blood pressure and in the pulse pressure, thesize of the pulse wave amplitude will not decrease necessarily.

The arrangement of the present embodiment that was arranged based on theabove knowledge shall be described next. As shown in FIG. 3, the presentembodiment is comprised of a sphygmomanometer unit 50, which isconnected to a cuff (arm band) and which detects the pulse wave from themeasured cuff pressure for the determination of the blood pressure, apersonal computer 60, which controls said sphygmomanometer unit 50 andwhich receives and processes the data measured by sphygmomanometer unit50, an output device 70, such as a display, printer or plotter, that isconnected to personal computer 60 and an input device 80, such as akeyboard, mouse or operation switch.

FIG. 1 shows the structural blocks of the sphygmomanometer 50 of thepresent embodiment. A capacitance type pressure sensor 12, a forcedexhaust valve 13, an air compressor pump 14 and a gradual exhaust valve15 are connected to an internal piping 11 which is in turn connected toa flexible tube 10a of cuff 10. Pressure sensor 12 is connected to acapacitance-frequency conversion circuit 16 which transmits the pressuredetection signal of a frequency that corresponds to the cuff pressure.The number of pressure detection signals for each predetermined timeinterval is counted by a gated counting circuit 17 and the counts areinputted into MPU (microprocessor unit) 18.

At each predetermined time interval, MPU 18 transmits an input controlsignal to gated counting circuit 17. Forced exhaust valve 13 is actuatedby the turning on and off of a solenoid and is driven via forced exhaustvalve driving circuit 19 by control signals from MPU 18. Air compressorpump 14 is a small rolling pump and is driven via pump driving circuit20 by control signals from MPU 18.

A communication interface circuit 21, that inputs and outputs measureddata and control codes, and an output circuit 22, for directlyoutputting data to an external storage device, etc., are connected toMPU 18. Communication interface circuit 21 is connected to input/outputcircuit part 60a of the personal computer 60 shown in FIG. 3. FIG. 2shows, in a functional manner, the means that are mainly realized bysoftware inside MPU 18 and personal computer 60. The cuff pressuredetection means 23, shown in FIG. 1 and comprising pressure sensor 12,capacitance-frequency conversion circuit 16 and gated counting circuit17, transmits the cuff pressure value C(i) shown in FIG. 4(a), forexample, at 50 msec intervals to pulse wave signal extraction means 24,blood pressure judging means 25 and cuff pressure storage means 26.

Of the cuff pressure values that are sequentially obtained from cuffpressure detection means 23, a predesignated number (for example, 5) ofthe latest cuff pressure values (for example, C(i-4), C(i-3), C(i-2),C(i-1) and C(i)) are stored in a constantly renewed manner by pulse wavesignal extraction device 24. The difference, between the latest cuffpressure value C(i) and the cuff pressure value C(i-4) preceding thelatest value by the predesignated number, is then calculated todetermine the difference signal d(i), shown in FIG. 4(b). Thereafter,the pulse wave component signal P(i), shown in FIG. 4(c), is computed byeliminating from said difference signal d(i), the influence of theaverage amount of pressure decrease that is calculated from a pluralityof cuff pressure values C(i) obtained within a predetermined time (forexample, 1 second). Besides using such a method to obtain pulse wavecomponent signal P(i), a signal equivalent to the pulse wave componentsignal P(i) can be obtained, for example, by extracting the pulse wavesignal directly from the cuff pressure value by means of a band filterand differentiating such a pulse wave signal.

The pulse wave component signal P(i) is transmitted to pulse waveamplitude detection means 27, pulse wave interval detection means 28 andaverage interval computing means 29. Pulse wave amplitude detectionmeans 27 cumulatively adds only those values of pulse wave componentsignal P(i) in the positive region for each pulse wave in order todetect the pulse wave amplitudes PA(I), shown in FIG. 4(d), andtransmits the PA(I) to the pulse wave amplitude storage means 32. Pulsewave interval detection means 28 determines the time, for example, atwhich the pulse wave component signal P(i) changes from being positiveto being negative, for each period to detect the time interval PT(I) ofthe pulse wave component on the basis of such a time and transmits thetime interval PT(I) to the pulse wave interval storage means 33. In thiscase, instead of determining the time interval, the sampling number ofcuff pressure values that corresponds to the time interval or theinterval of the value of the cuff pressure value C(i) that correspondsto each time, in other words, the pressure interval, can be detected andused as the time interval PT(I).

An average interval computing means 29, an amplitude quantization means30 and an interval quantization means 30 may be provided to lighten thedata load to be stored by the said pulse wave amplitude storage means 32and pulse wave interval storage means 33. Average interval computingmeans 29 computes the average value of the pulse wave periods in pulsewave component signal P(i) and transmits the value, obtained byaccumulating a predetermined number of pulse wave intervals (forexample, the 6 pulse wave intervals computed immediately after the startof measurement) and dividing with the predetermined number, as theaverage interval PTS to interval quantization means 31. In the casewherein sampling numbers or pressure intervals are detected by pulsewave interval detection means 29 as mentioned above, average intervalcomputing means 29 detects the sampling number or the average pressureinterval that correspond to the average time interval.

At interval quantization means 31, the pulse wave intervals PT(I) arecompared with average interval PTS and are associated with a number ofinterval sections to reduce the amount of data. For example, ifPT(I)>2PTS then N(I)=3, if 2PTS>PT(I)>1.5PTS then N(I)=2, if1.5PTS>PT(I)>0.5 PTS then N(I)=1 and if 0.5PTS>PT(I) then N(I)=0, whereN(I) is the quantized pulse wave interval.

The pulse wave amplitude PA(I) that is outputted by the said pulse waveamplitude detection means 27 may also be converted to a quantizedamplitude value by the association of each pulse wave amplitude PA(I)with a number of amplitude sections by means of amplitude quantizationmeans 30. The interval and amplitude quantization means 30 and 31 reducethe load in terms of volume and time of subsequent data processing(including data storage) by cutting off the unnecessary resolution ofthe detected value. The resolution of the data after quantization is setas appropriate according to the detection accuracy required. Obviously,if there are no problems in the load in terms of volume and time, thesaid quantization means are unnecessary.

The pulse wave amplitudes PA(I) are inputted along with the cuffpressures C(i) into blood pressure judging means 25 and the systolicpressure Pmax, the diastolic pressure Pmin, the mean blood pressurePave, the pulse rate, etc. are computed by real time processing. Forexample, the mean blood pressure Pave is determined as the cuff pressureC(imax) at the point at which the maximum value PA(Imax) of the pulsewave amplitudes PA(I) was obtained, the systolic pressure Pmax isdetermined as the cuff pressure C(is) at the point at which a pulse waveamplitude PA(Is), corresponding to a predetermined percentage S % of themaximum value PA(Imax), was obtained at the higher pressure side of thepoint at which PA(Imax) was obtained, and the diastolic pressure Pmin isdetermined as the cuff pressure C(id) at the point at which a pulse waveamplitude PA(Id), corresponding to a predetermined percentage D % of themaximum value PA(Imax), was obtained at the lower pressure side of thepoint at which PA(Imax) was obtained. In other words:

    PA(Imax)×S/100=PA(Is)

    PA(Imax)×D/100=PA(Id)

The output of blood pressure judging means 25 is inputted into bloodpressure storage means 34 which stores the blood pressure values. Forexample, the addresses of the data stored in pulse wave amplitudestorage means 32 and cuff pressure storage means 26 are stored.

The said procedures of each means are carried out in real time and themeasurement is completed when the diastolic pressure is judged.Thereafter, processes such as the display of the blood pressure and theclassification of the pattern are carried out on the basis of datastored in storage means 26, 32, 33 and 34. Of the functional blocksshown in FIG. 2, the data processing part X and the blood pressurecomputing part Y are executed by MPU 18 within sphygmomanometer unit 50and the pattern judging part Z, that shall be described later, isexecuted by the personal computer 60 shown in FIG. 3.

The actual operation of MPU 18 is started by the start command which istransmitted from personal computer 60 as a result of an input from inputdevice 80. By the start command, MPU 18 closes forced exhaust valve 13,starts up air compressor pump 14 and raises the pressure within cuff 10to a preset pressure setting (for example, 140 mmHg). It is possible topreset the initial value of the pressure setting and if the pressure isnot sufficient, recompression is performed by automatically increasingthe pressure in up to 2 stages and by 30 mmHg per stage. When thepressure of the interior of cuff 10 is raised to the pressure setting,air compressor pump 14 is stopped and the sampling of the measuredpressure values is started. Gradual exhaust valve 15 reduces thepressure within cuff 10 at a rate of approx. 3˜6 mEg/second. The cuffpressure values are sampled in intervals of approx. 50 msec and uponeach sampling, counting circuit 17 takes in the pressure detectionsignal of capacitance-frequency conversion circuit 16 for approximately8.2 msec and counts the number of incoming pulses during this time. Suchsampling of measured values is continued in parallel with thecomputation of the mean blood pressure, the systolic pressure and thediastolic pressure and the measurement ends at the point at which thediastolic pressure is obtained.

The pulse wave amplitudes PA(I), that are stored in the said pulse waveamplitude storage means 32, and the pulse wave intervals PT(I), that arestored in the said pulse wave interval storage means 33, are inputtedinto pulse wave pattern generation means 35 and, if necessary, pulsewave patterns, that are suited for the pattern comparison operation, aregenerated according to the reference values in reference value storagemeans 36 and are outputted to output device 70 and transmitted to pulsewave pattern classification means 37. Reference value storage means 36usually stores and holds a number of typical examples of pulse wavepatterns, in other words, reference patterns and, if necessary, alsostores the scale of the reference pattern and other reference valuesthat indicate the characteristics of the reference pattern.

The pulse wave pattern classification means 37 compares the pulse wavepattern generated by pulse wave pattern generation means 35 with aplurality of reference patterns stored by reference pattern storagemeans 36 and classifies the pulse wave pattern as one of the referencepatterns. Besides the method to be described later in which the pulsewave pattern and reference patterns are compared by direct comparison ofentire patterns, methods may be used in which the classification isperformed by using reference values extracted from the reference patternas classification references or in which the classification is performedby detecting peak widths and number of peaks (classification referencesfor patterns A, C and E shown in FIG. 9), intervals of peak amplitudes(classification reference for patterns A and D shown in FIG. 9), etc. onthe basis of reference values stored in advance in a storage means.

FIG. 9 shows 5 pulse wave pattern types, A to E, as typical examples ofpulse wave patterns. A reference pattern, a pulse wave pattern thatcorresponds to each reference pattern and clinical cases that arethought to correspond to each reference pattern are shown for each type.These reference patterns are stored in the later mentioned referencepattern storage means 36 as typical examples that were extracted fromstatistical processing of a large number of cases. It is also possible,for example, to add modifications to the said plurality of referencepatterns on the basis of pulse wave patterns of normal conditions thatare registered according to each individual in order to reduce theinfluence of individual differences on the judgement.

FIG. 10 shows the processing procedure that is carried out at pulse wavepattern generation means 35. First, the pulse wave amplitudes PA(I) andthe pulse wave intervals PT(I) are read in (1001, 1002) and the pulsewave amplitudes PA(S) (S is the sample number), shown in FIG. 4(e), aredetermined by interpolating the interval between the values of eachpulse wave amplitude PA(I) by a straight line or a sine curve (1003).Here, the maximum sample number S is the number of data required toimprove the display conditions and to secure the required amount ofinformation for the pattern classification to be described later. Inthis case, the sample number S may, for example, be set equal to thesampling number i of the cuff pressure detection data. Next, the pulsewave amplitudes PA(S) are smoothed by calculating simple averages:

    {P(S-1)+P(S)+P(S+1)}/3→P(S)

or weighted averages:

    {P(S-1)+2P(S)+P(S+1)}/4→P(S)

or moving averages (1004). Such processes for data interpolation andfiltering/smoothing are expressed visually in FIG. 12. Here, it ispreferable to perform the prior process shown in FIG. 11 beforeperforming the data interpolation process shown in FIG. 12. This isbecause large measurement errors, such as PA(Ie)=Pe, may arise in thepulse wave amplitudes PA(I) due to movement of the body by the subjectduring the measurement. Such erroneous data should be eliminated priorto data interpolation and filtering/smoothing since such data will bringabout a bad effect on the subsequent processes. This process isperformed when a difference that is no less than a predetermined amountor a predetermined percentage arises between PA(I) and a reference valuecomputed from the data prior and subsequent to PA(I).

For example, the value of PA(I) is compared to a reference value (forexample an average, a moving average, etc.) calculated from n prior dataand n subsequent data (for example, if n=3, the 6 data of PA(I-3),PA(I-2), PA(I-1), PA(I+1), PA(I+2), PA(I+3)) and if the differencebetween the measured data and the reference value exceeds apredetermined value (for example, if the difference is 30% or more ofthe reference value), the measured value is judged to be an outlyingdata and, as shown in the graph at the bottom of FIG. 12, the measureddata Pe is replaced by reference value Pc. In the case of data at bothends, for which the reference value for PA(I) cannot be calculated, inother words in the case I≦n or I≧Im-n+1 (Im is the number of pulse waveamplitude data), the reference value may be calculated by decreasing thenumber n or the amplitude data in the range, I≦n and I≧Im-n+1, may beeliminated and such parts at both ends may be removed from beingsubjected to subsequent processes.

After the filtering/smoothing process, the normalization of the pulsewave interval and the normalization of the pulse wave amplitude areperformed as indicated by 1005 and 1006 in FIG. 10. In this case, if thenormalization constants for the pulse wave interval and pulse waveamplitude are both set to 100, as shown in FIG. 13, the maximum samplenumber Sm and the maximum amplitude Pm of pulse wave pattern PA(S) isdetermined and sample number S is multiplied by (100/Sm) and pulse waveamplitude PA(S) is multiplied by (100/Pm) to obtain the pulse wavepattern PAP, which is normalized to a maximum sample number of 100 and amaximum amplitude of 100 and is shown by the dotted line in the diagram.This is also shown in FIG. 4(f). Here, the normalization constantmatches the maximum sample number and maximum amplitude of the referencepattern shown in FIG. 13 and by comparing pulse wave pattern PAP to thereference pattern, the differences in shape can be determinedaccurately. The reference pattern is stored in reference value storagemeans 36, for example, by storing the coordinates of the plurality ofpoints of the envelope of the pattern and the interval between pointsmay interpolated by a straight line or sine curve, etc. when carryingout the classification procedure to be described later. The saidnormalization constant may be read out as a reference value fromreference value storage means 36 upon performing the normalizationprocess (1005, 1006). The pulse wave pattern PAP is outputted to outputdevice 70 from personal computer 60 and, for example, is displayed on adisplay and becomes the data subjected to the pattern classificationprocess described below.

The said normalization of measured data is performed to facilitate theclassification by comparison of the reference pattern with the pulsewave pattern (this includes both the classification procedure describedbelow and the case in which the physician diagnoses a pulse wave patternthat is simply displayed on a display or a printer). This is becausevarious alterations may arise in the pulse wave pattern actuallymeasured due to such factors as the amount of subcutaneous fat of thepatient, the attachment condition of the cuff and the time ofmeasurement (day, noon, night, etc.) and because, in the case of gradualexhaust valves in which the usual rate control is not performed, themeasurement speed may vary due to variations in the rate of reduction ofthe cuff pressure.

In particular, a case may arise wherein the peak value Pm appears atdifferent positions in the reference pattern and the measured pulse wavepattern. This may occur since the mean blood pressure and elasticmodulus of the blood vessel differ widely for different subjects. Insuch a case, the normalization of the pulse wave interval, shown in FIG.14, is performed. In this process, the position Sp, at which the peakvalue appears (PA(Sp)=Pm), is used as a basis to normalize each of thesections 1˜Sp and Sp˜Sm with respect to the reference pattern. Forexample, as shown in FIG. 14, if the width corresponding to section 1˜Spof the reference pattern is assumed to be 44 and the width correspondingto section Sp˜Sm of the reference pattern is assumed to be 55, thefollowing calculation is performed on the original sample numbers S ofthe measured pulse wave pattern:

in the range 1≦S<Sp,

    S'=(44/Sp)·S

and in the range Sp≦S≦Sm,

    S'={55/(Sm-Sp)}·(S-Sp)+45

The peak position of the pulse wave pattern PA(S'), shown by the dottedline in FIG. 14, is thus matched with that of the reference pattern anderrors in the classification due to deviations in the peak position maytherefore be prevented in the classification procedure described later.

The processing procedure performed at pulse wave pattern classificationmeans 37 shall be described next. As shown in FIG. 15, the referencepatterns SPA(n) and the reference values SVA(m) are read in fromreference value storage means 36 (1011, 1012). Here, the entirereference pattern SPA(n) is normalized by the said normalizationconstant. Next, the outlying factor EPT for the pulse wave intervalsPT(I) is computed (1013). The outlying factor EPT is the number of I'sfor which the condition SVA(1)>PT(I)/PT(I-1)>SVA(2) is not satisfied andthe values of SVA(1) and SVA(2), which stipulate the upper and lowerlimits respectively, are determined from statistical data. Arrhythmiamay be presumed in cases wherein the ratio of sequential pulse waveintervals PT(I)/PT(I-1) is outside the said condition at many points.Thus, in cases wherein the outlying factor EPT is greater than referencevalue SVA(3), the pulse wave pattern is classified as pattern D, shownin FIG. 9 (1014). The reference value SVA(3) is also determinedappropriately from statistical data.

If outlying factor EPT is less than reference value SVA(3), the pulsewave pattern PAP is compared with reference patterns SPA(n) (1015). Thereference pattern SPA(n) is that which corresponds to pattern A orpattern B when n=1, to pattern C when n=2 and to pattern E when n=3.Here, the square of the deviations of the amplitudes of pulse wavepattern PAP and amplitudes of the respective reference patterns SPA(n)are summed over all sample numbers to compute pattern error EPA(n). Thatis, ##EQU1##

The correlation between pulse wave pattern PAP and reference patternSPA(n) may also be determined from the summation of deviations and othermethods.

Next, the least of the pattern errors EPA(n) is judged (1016) and set asEPA(N). If N=1 and if the maximum value Pm of the pulse wave amplitudes(the maximum amplitude before normalization) is greater than a referencevalue SVA(4), a flag is placed on pattern A while if Pm is less thanSVA(4), a flag is placed on pattern B. If N=2, a flag is placed onpattern C and if N=3, a flag is placed on pattern E. The said referencepatterns SPA(n) and reference values SVA(m) should be set appropriatelyand statistically on the basis of numerous measurement examples and itis preferable to be able to modify these appropriately for a specificindividual when necessary.

The pulse wave pattern PAP and the result of pattern classification,obtained by the method described above, are displayed at output device70 shown in FIG. 3. This output device 70 displays the cuff pressure,the pulse wave component and the pulse wave amplitudes in real timeduring blood pressure measurement and simultaneously displays each ofthe blood pressure values, the pulse rate, the classified pattern, thepulse wave pattern itself and the plurality of reference patterns shownin FIG. 9 after the measurement.

Although the MPU 18 for blood pressure measurement and the personalcomputer 60 for data processing are provided separately as shown in FIG.3 in the present embodiment, both the real time processing for bloodpressure measurement and the pulse wave pattern processing may also beperformed with one computing device.

By the present embodiment, the pulse wave pattern is displayed at adisplay or some other output device 70 and, at the same time, isclassified only on the basis of the shape of the pulse wave patternusing means that use predetermined criteria, for example, normalization.Furthermore, the classification is also performed on the basis of themagnitudes of the pulse amplitudes prior to being normalized as a pulsewave pattern. By eliminating the effects of detection errors due tonoise, etc. by interpolation and smoothing of the pulse wave pattern andby combining such processes with the normalization of the pattern,information on the vascular dynamics, in particular, information on theexpandability of the blood vessel, can be derived regardless ofmeasurement conditions or individual differences (differences in pulserate, blood output, skinfold thickness, blood pressure amplitude anddifference between systolic and diastolic pressures). Furthermore, thedisplaying of normalized pulse wave patterns enables the estimation ofthe reliability of blood pressure values, etc. through comparisons ofpatterns and enables accurate judgements that are not mislead by asimple indication of just numbers. The operation command forsphygmomanometer unit 50 is transmitted from personal computer 60 and,furthermore, the display and storage of measured data and classificationpatterns and the display of explanations of the operation procedure areexecuted under the control of personal computer 60 on the basis ofinputs from input device 80.

A different embodiment of the said pattern classification means 37 shallnow be described with reference to FIGS. 16 to 18. FIG. 16 shows theoverall structure of a classification procedure based on pulse wavepatterns. Although pulse wave pattern PAP obtained through the pulsewave pattern generation procedure shown in FIG. 10 can be classified bythis classification procedure, the pulse wave amplitude PA(I), shown inFIG. 3(d), is classified directly instead of normalized pattern PAP inthis procedure. First, the pulse wave amplitude PA(I) is smoothed by apredetermined method (1021), for example by weighted averaging with apredetermined number of prior and subsequent data, and then the peaksand the disturbance of the smoothed pulse wave amplitude PA(I) aredetected (1022). FIG. 17 shows the procedure for detecting the peaks anddisturbance. First, the variable Cpeak, which expresses the number ofpeaks in the pattern of pulse wave amplitudes PA, the variable I, thatindicates the data number of a pulse amplitude PA(I), the variablesPeak(l), . . . , Peak(m) (m is the number of peaks), which indicate theposition of the peaks in pulse wave pattern PA by means of data numberI, and the variable Cvibra, which indicates the degree of disturbance ofthe pulse wave amplitudes PA(I), are initialized (10221).

Next, the Ith pulse wave data PA(I) and the immediately preceding pulsewave data PA(I-1) are compared by means of 2 parameters, n4 and n5(10222). Here n4 is a proportionality constant slightly larger than 1which is multiplied to the absolute value of pulse wave amplitude PA andn5 is a shift quantity which does not depend on the value of pulse waveamplitude PA. If PA(I) has increased with respect to PA(I-1) by just apredetermined amount determined from the preset values of n4 and n5, theprocess moves on to procedure 10223 and if not so, the process moves onto procedure 10225. In procedure 10223, pulse wave amplitudes PA(I) andPA(I+1) are compared using the same parameters n4 and n5 and if PA(I+1)has decreased with respect to PA(I) by just a predetermined amount, theprocess moves on to 10224 and if not so, the process moves on toprocedure 10225. n4 is a constant for eliminating the noise proportionalto the absolute value of wave pulse amplitude PA and n5 is a constantfor eliminating the noise that is not proportional to the absolute valueof pulse amplitude PA and these parameters are set appropriately to suitthe data measurement system and the data processing system.

In procedure 10224, it is deemed that a pulse amplitude peak has beendetected and the number of peaks Cpeak is incremented by 1 and the valueof peak position peak(Cpeak) is set to I. After thus detecting whetheror not the data is a peak of the pulse wave pattern, the process moveson to the procedure for detecting the degree of disturbance of the pulsewave pattern. In procedure 10225, pulse wave data PA(I) and theimmediately preceding pulse wave data PA(I-1) are compared and if PA(I)has not increased with respect to PA(I-1) by or by more than apredetermined increase amount determined from parameters n6 and n7, theprocess moves on to procedure 10228 and if not so, the process moves onto procedure 10226. In procedure 10226, the pulse wave amplitude PA(I)and the immediately preceding amplitude PA(I-1) are compared and ifPA(I) has not decreased with respect to PA(I-1) by or by more than apredetermined decrease amount determined from parameters n8 and n9, theprocess moves on to 10228 and if not so, the process moves on toprocedure 10227. In procedure 10227, it is deemed that pulse waveamplitude PA(I) has changed largely with respect to immediatelypreceding data PA(I-1) and the degree of disturbance Cvibra isincremented by 1. Here, the values of n6, n7, n8 and n9 are setappropriately from statistical data.

By the above process, the presence or non-presence of a peak ordisturbance at the Ith pulse wave amplitude PA(I) is judged and theprocess is carried out on the next (I+1)th data at procedure 10228. Thedetection of the number of peaks Cpeak, the peak positions Peak(Cpeak)and the degree of disturbance Cvibra of the entire pattern is thuscompleted when all of the pulse wave amplitudes PA(I) from I=1 to n havebeen processed as described above.

Thereafter, the process returns to the procedure in FIG. 16 again anddegree of disturbance Cvibra and a predetermined value n1 are comparedat procedure 1023 and if degree of disturbance Cvibra is equal to orgreater than predetermined value n1, a flag is placed on pattern D.Next, it is judged whether or not the number of peaks Cpeak is 2 orgreater and if there are 2 or more peaks, a flag is placed on pattern E.

Next, the calculation of the peak width is performed in procedure 1025.The calculation of the peak width is carried out by the procedure shownin FIG. 18 on the basis of the peak positions detected in procedure1022. First, m is set equal to 1 in Procedure 10251 and the value of thepulse wave amplitude PA(Peak) at a peak position is compared with thepulse wave amplitude PA(Peak-m) at a position m data prior to the peakposition to judge whether PA(Peak-m) is equal to or greater than thevalue obtained by multiplying PA(Peak) by a parameter n10. If PA(Peak-m)is equal to or greater than PA(Peak) times n10, m is incremented by 1and procedure 10252 is carried out again. Judgements are thus performeduntil the judgement result at procedure 10252 becomes negative and whenPA(Peak-m) becomes less than PA(Peak) times n10, the process moves on toprocedure 10253. Here, n10 is a value that is usually somewhat less than1 and is set appropriately from statistical data.

At procedure 10253, k is set equal to 1 and at procedure 10254, it isjudged whether PA(Peak+k) is equal to or greater than PA(Peak) timesn10. If PA(Peak+k) is equal to or greater than PA(Peak) times n10, k isincremented by 1 and the judgement in procedure 10254 is carried outagain. Judgements are thus carried out until the judgement result atprocedure 10254 becomes negative and when PA(Peak-k) becomes less thanPA(Peak) times n10, the peak width Pwidth is determined by adding thesaid m and k at procedure 10255.

After determining the peak width Pwidth in the manner above, the processmoves on to procedure 1026 in FIG. 16 and it is judged whether Pwidth isequal to or greater than n2. Here, parameter n2 is set appropriatelyaccording to statistical data. If peak width Pwidth is equal to orgreater than n2, it is judged whether systolic pressure Pmax is equal toor greater than 100 and if systolic pressure Pmax is equal to or greaterthan 100, a flag is placed on pattern C while if systolic pressure Pmaxis less than 100, a flag is placed on pattern B (1027). On the otherhand, if peak width Pwidth is less than n2, it is judged whether thepulse wave amplitude PA(Peak) of the peak is equal to or greater than n3(1028). Here, n3 is set appropriately according to statistical data. Ifpeak data PA(Peak) is equal to or greater than n3, a flag is placed onpattern A and the process ends. If peak data PA(Peak) is less than n3,it is judged whether systolic pressure value Pmax is equal to or greaterthan 100 (1029) and if systolic pressure value Pmax is equal to orgreater than 100, flags are placed on both pattern A and pattern B whileif systolic pressure Pmax is less than 100, a flag is placed only onpattern B.

The classification pattern is then displayed at an output device 70 suchas a display in accordance with the flag placed at each pattern in themanner described above. Thus, by the detection of the number andpositions of peaks, the degree of disturbance and the peak width, thesaid classification procedure shown in FIG. 16 enables rapid and simplejudgement of classification patterns without detailed inspection of theentire data of the reference and pulse wave patterns. In particular, byperforming the judgement of patterns D and E by detecting the number ofpeaks and degree of disturbance, it becomes possible to judge suchanomalous data infallibly.

Unlike the usual anomalous data, it is difficult to make judgements inthe classification of patterns A, B and C. However, these patterns canbe classified accurately by using the data of the systolic pressurevalue Pmax. For example, even if peak width Pwidth is equal to orgreater than n2, if systolic pressure value Pmax is small, it is aclinical error to deem the pattern to be pattern C and the patternshould be judged to be pattern B. Also, the classification of pattern Aand pattern B should be performed on the basis of both systolic pressurePmax and maximum value Pm (=PA(Peak)) of the pulse wave amplitudes. Forexample, if systolic pressure Pmax is no more than 100 and if maximumvalue Pm of the pulse wave amplitude is approximately 1/3 or less of theusual value (statistical mean) at the same time, the pattern may beclassified as pattern B. However, if only one of the above conditionsare met, a more appropriate classification result is that the patterncorresponds to both pattern A and pattern B.

The measured pulse wave pattern may thus be classified as correspondingto 2 or more of the said classification patterns by the classificationprocedure shown in FIG. 16. In this case, for example, if the subjectmoves his/her body during the measurement, the pulse wave pattern maybecome disrupted and be classified as corresponding to pattern C, D or Eeven if the subject is normal. However, since there are cases ofmultiple symptoms and intermediate cases, pulse wave patterns should beclassified as corresponding to 2 or more reference patterns in suchcases. Also, since the purpose of the said pattern classification is notto determine the final diagnosis result but is to call the necessaryattention to the subject and the person diagnosing to promote a moreaccurate diagnosis than was possible formerly and to avoid pathologicaldangers, that a measured pattern is classified as corresponding to aplurality of reference patterns does not lower the value of the presentinvention by any means.

Although 2 typical examples of pattern classification procedures weredescribed in the embodiment above, the present invention is not limitedby the said classification procedures and may be carried out by otherclassification procedures. An example is a method in which the slopes,of a straight line joining a point on the pattern that indicates thesaid maximum value Pm of PA(Sp) and a point on the pattern thatindicates a value of PA(S) for which S≠Sp, are scanned sequentially fromS=Sp in the forward and reverse directions as shown in FIGS. 19 to 22.In this method, the measured pattern is deemed to correspond to eitherpattern A or B if the values of the slopes are within a certain range asshown in FIG. 19. If, as shown in FIG. 20, the slope changes largely inthe vicinity of S=Sp, the measured pattern corresponds to pattern E. If,as shown in FIG. 21, the slope is small in the vicinity of S=Sp andbegins to increase some distance away from S=Sp, the measured patterncorresponds to pattern C. If, as shown in FIG. 22, the width ofdeflection of the slope is large or the slope deflects randomly, themeasured pattern corresponds to pattern D. Thus, it is adequatelypossible to classify patterns according to the manner of variation ofthe slope angles by determining the slope angles of lines connectingpoints on the pattern in the manner above.

Although the pattern classification procedures in each of theembodiments described above were carried out by judging which of the 5typical reference patterns the pulse wave pattern based on measured dataresembled most closely, the reference patterns are not limited to thosementioned above and, if necessary, the physician may set his/her ownunique reference patterns for each individual patient. Referencepatterns that are different from those mentioned above may also be setby statistically processing the data measured for several patients. Insuch cases, 6 or more or less than 5 reference patterns may be set. Fromthe data from preliminary tests performed by the present inventors, itwas found that is possible to classify the measured data intoapproximately 10 or more patterns and to presume, in medical terms, theconditions of the circulatory system that can be associated with each ofthese patterns. On the other hand, there may be cases whereinmeasurements are made on the basis of a specific purpose. For example,if measurements are to be made only for the purpose of diagnosingarteriosclerosis, a relatively few number of reference patterns, forexample, 2 or 3 patterns, may be prepared from the peak height, peakwidth, shape of the tip of the peak, etc. to carry out theclassification.

Industrial Application

As described above, since the present invention is characterized bygenerating patterns of variations of pulse wave amplitudes and byclassifying such patterns according to reference patterns or referencevalues or normalizing the pattern with a predetermined reference value,the present invention presents the following effects:

(1) Not only can pulse wave patterns be used to simply judge the bloodpressure as was done conventionally, but the shapes of pulse wavepatterns can be classified on the basis of hemodynamic references.

(2) The provision of a pulse wave pattern normalization means enablesthe recognition of only the shapes of pulse wave patterns which varywidely due to measurement conditions and individual differences. Inparticular, when a pulse wave pattern classification means is provided,it becomes possible to perform appropriate classification on the basisof only the pattern shapes.

(3) By setting a plurality of reference patterns, particularly accordingto peak shape, for the classification of pulse wave patterns, it becomespossible to obtain information on the expandability, etc. of bloodvessels.

(4) By providing a means of quantizing the detected data, it becomespossible to priorly eliminate the amount of data that is unnecessary forsubsequent pattern generation and classification and thus to reduce theprocessing time and the memory capacity.

(5) By detecting the peak and the degree of disturbance in theclassification of pulse wave patterns, it becomes possible, particularlyin the classification of anomalous patterns, to make the processing morerapid and simple.

(6) By detecting the peak width in the classification of pulse wavepatterns, the classification process, that is pursuant to blood vesselconditions that are hard to distinguish, can be carried out infallibly.

(7) By using the simultaneously detected systolic pressure value as partof the classification references in the classification of pulse wavepatterns, the classification process, that is pursuant to outputstrengths and blood vessel conditions that are difficult to distinguish,can be carried out accurately.

What is claimed is:
 1. An electronic pressure detecting device formonitoring hemodynamic states of a patient based on dynamiccharacteristics of blood vessels or cardiac output characteristicscomprising:a cuff for applying cuff pressure to said patient; pressuredetection means for detecting said cuff pressure and pulse wavesoverlaid on said cuff pressure while said cuff pressure is graduallyincreased decreased; pulse wave extraction means for extracting pulsewave components from said detected cuff pressure; pulse wave amplitudedetection means for detecting pulse wave amplitudes of said extractedpulse wave components; pulse wave interval detection means for detectingpulse wave intervals which correspond to time intervals or pressureintervals between adjacent extracted pulse wave components; pulse wavepattern generation means for generating pulse wave patterns based onsaid pulse wave amplitudes and said pulse wave intervals; patternclassification means for classifying said pulse wave patterns into oneor more categories based on comparison with a plurality of predeterminedhemodynamic reference patterns that correspond to particular dynamiccharacteristics of blood vessels or cardiac output characteristic eachcategory representing a different hemodynamic condition; and displaymeans for displaying said generated pulse wave patterns and informationabout said one or more categories into which said pulse wave patternsare classified.
 2. An electronic pressure detecting device formonitoring hemodynamic states of a patient based on dynamiccharacteristics of blood vessels or cardiac output characteristicscomprising:a cuff for applying cuff pressure to said patient; pressuredetection means for detecting said cuff pressure and pulse wavesoverlaid on said cuff pressure while said cuff pressure is graduallyincreased or decreased; pulse wave extraction means for extracting pulsewave components from said detected cuff pressure; pulse wave amplitudedetection means for detecting pulse wave amplitudes of said extractedpulse wave components; pulse wave pattern generation means forgenerating pulse wave patterns that graphically express variations insaid detected pulse wave amplitudes while said cuff pressure isgradually decreased or increased; pattern classification means forclassifying said pulse wave patterns into one or more categories basedon comparison with a plurality of predetermined hemodynamic referencepatterns that correspond to particular dynamic characteristics of bloodvessels or cardiac output characteristic each category representing adifferent hemodynamic condition; and display means for displaying saidgenerated pulse wave patterns and information about said one or morecategories into which said pulse wave patterns are classified.
 3. Anelectronic pressure detecting device as set forth in claim 1 or in claim2, wherein said pattern classification means is provided with means fordetecting numbers of peaks or degrees of disturbance of said pulse wavepatterns for use as part of said reference patterns duringclassification of said pulse wave patterns.
 4. An electronic pressuredetecting device as set forth in claim 1 or in claim 2, wherein saidpattern classification means is provided with means for detecting peakwidths of said pulse wave patterns for use as part of said referencepatterns during classification of said pulse wave patterns.
 5. Anelectronic pressure detecting device as set forth in claims 1 or inclaim 2, further comprising blood pressure detection means for detectingat least systolic pressure based on said extracted pulse wave componentsor said generated pulse wave patterns, wherein said patternclassification means classifies said pulse wave patterns using saiddetected systolic pressure as part of said reference patterns.